If you get an error that looks like ```../kernel/x86_64/dgemm_kernel_4x4_haswell.S:1709: Error: no such instruction: `vpermpd $ 0xb1,%ymm0,%ymm0'```, then you need to set `OPENBLAS_DYNAMIC_ARCH = 0` or `OPENBLAS_NO_AVX2 = 1`, or you need a newer version of `binutils` (2.18 or newer). ([Issue #7653](https://github.com/JuliaLang/julia/issues/7653)) Illegal Instruction error | Check if your CPU supports AVX while your OS does not (e.g. through virtualization, as described in [this issue](https://github.com/JuliaLang/julia/issues/3263)). ### OS X You need to have the current Xcode command line utilities installed: run `xcode-select --install` in the terminal. You will need to rerun this terminal command after each OS X update, otherwise you may run into errors involving missing libraries or headers. You will also need a 64-bit gfortran to compile Julia dependencies. The gfortran-4.7 (and newer) compilers in Brew, Fink, and MacPorts work for building Julia. Clang is now used by default to build Julia on OS X 10.7 and above. On OS X 10.6, the Julia build will automatically use `gcc`. On current systems, we recommend that you install the command line tools as described above. Older systems do not have a separate command line tools package from Apple, and will require a full Xcode install. On these, you will need at least Xcode 4.3.3. In Xcode prior to v5.0, you can alternatively go to Preferences -> Downloads and select the Command Line Utilities. These steps will ensure that clang v3.1 is installed, which is the minimum version of `clang` required to build Julia. If you have set `LD_LIBRARY_PATH` or `DYLD_LIBRARY_PATH` in your `.bashrc` or equivalent, Julia may be unable to find various libraries that come bundled with it. These environment variables need to be unset for Julia to work. If you see build failures in OpenBLAS or if you prefer to experiment, you can use the Apple provided BLAS in vecLib by building with `USE_SYSTEM_BLAS=1`. Julia does not use the Apple provided LAPACK, as it is too old. When building Julia, or its dependencies, libraries installed by third party package managers can redirect the compiler to use an incompatible version of the software it is looking for. One example of this happening is when a piece of software called the "linker" gives an error involving "Undefined symbols." If that happens, you can usually figure out what software package is causing the error from the names in the error text. This sort of error can be bypassed by, temporarily, uninstalling the offending package. If the offending package cannot be uninstalled by itself, it may be possible to just uninstall the development headers (for example: a package ending in "-dev" in Fink). ### FreeBSD Clang is the default compiler on FreeBSD 11.0-RELEASE and above. The remaining build tools are available from the Ports Collection, and can be installed using `pkg install git gcc gmake cmake`. To build Julia, simply run `gmake`. (Note that `gmake` must be used rather than `make`, since `make` on FreeBSD corresponds to the incompatible BSD Make rather than GNU Make.) As mentioned above, it is important to note that the `USE_SYSTEM_*` flags should be used with caution on FreeBSD. This is because many system libraries, and even libraries from the Ports Collection, link to the system's `libgcc_s.so.1`, or to another library which links to the system `libgcc_s`. This library declares its GCC version to be 4.6, which is too old to build Julia, and conflicts with other libraries when linking. Thus it is highly recommended to simply allow Julia to build all of its dependencies. If you do choose to use the `USE_SYSTEM_*` flags, note that `/usr/local` is not on the compiler path by default, so you may need to add `LDFLAGS=-L/usr/local/lib` and `CPPFLAGS=-I/usr/local/include` to your `Make.user`, though doing so may interfere with other dependencies. Note that the x86 architecture does not support threading due to lack of compiler runtime library support, so you may need to set `JULIA_THREADS=0` in your `Make.user` if you're on a 32-bit system. ### Windows In order to build Julia on Windows, see [README.windows](https://github.com/JuliaLang/julia/blob/master/README.windows.md). ### Vagrant Julia can be developed in an isolated Vagrant environment. See [the Vagrant README](https://github.com/JuliaLang/julia/blob/master/contrib/vagrant/README.md) for details. ## Required Build Tools and External Libraries Building Julia requires that the following software be installed: - **[GNU make]** — building dependencies. - **[gcc & g++][gcc]** (>= 4.7) or **[Clang][clang]** (>= 3.1, Xcode 4.3.3 on OS X) — compiling and linking C, C++. - **[libatomic][gcc]** — provided by **[gcc]** and needed to support atomic operations. - **[python]** (>=2.7) — needed to build LLVM. - **[gfortran]** — compiling and linking Fortran libraries. - **[perl]** — preprocessing of header files of libraries. - **[wget]**, **[curl]**, or **[fetch]** (FreeBSD) — to automatically download external libraries. - **[m4]** — needed to build GMP. - **[awk]** — helper tool for Makefiles. - **[patch]** — for modifying source code. - **[cmake]** (>= 3.4.3) — needed to build `libgit2`. - **[pkg-config]** — needed to build `libgit2` correctly, especially for proxy support. On Debian-based distributions (e.g. Ubuntu), you can easily install them with `apt-get`: ``` sudo apt-get install build-essential libatomic1 python gfortran perl wget m4 cmake pkg-config ``` Julia uses the following external libraries, which are automatically downloaded (or in a few cases, included in the Julia source repository) and then compiled from source the first time you run `make`: - **[LLVM]** (3.9 + patches) — compiler infrastructure (see [note below](#llvm)). - **[FemtoLisp]** — packaged with Julia source, and used to implement the compiler front-end. - **[libuv]** (custom fork) — portable, high-performance event-based I/O library. - **[OpenLibm]** — portable libm library containing elementary math functions. - **[DSFMT]** — fast Mersenne Twister pseudorandom number generator library. - **[OpenBLAS]** — fast, open, and maintained [basic linear algebra subprograms (BLAS)](https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms) library, based on [Kazushige Goto's](https://en.wikipedia.org/wiki/Kazushige_Goto) famous [GotoBLAS](https://www.tacc.utexas.edu/research-development/tacc-software/gotoblas2) (see [note below](#blas-and-lapack)). - **[LAPACK]** (>= 3.5) — library of linear algebra routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. - **[MKL]** (optional) – OpenBLAS and LAPACK may be replaced by Intel's MKL library. - **[SuiteSparse]** (>= 4.1) — library of linear algebra routines for sparse matrices (see [note below](#suitesparse)). - **[ARPACK]** — collection of subroutines designed to solve large, sparse eigenvalue problems. - **[PCRE]** (>= 10.00) — Perl-compatible regular expressions library. - **[GMP]** (>= 5.0) — GNU multiple precision arithmetic library, needed for `BigInt` support. - **[MPFR]** (>= 3.0) — GNU multiple precision floating point library, needed for arbitrary precision floating point (`BigFloat`) support. - **[libgit2]** (>= 0.23) — Git linkable library, used by Julia's package manager. - **[curl]** (>= 7.50) — libcurl provides download and proxy support for Julia's package manager. - **[libssh2]** (>= 1.7) — library for SSH transport, used by libgit2 for packages with SSH remotes. - **[mbedtls]** (>= 2.2) — library used for cryptography and transport layer security, used by libssh2 - **[utf8proc]** (>= 2.1) — a library for processing UTF-8 encoded Unicode strings. - **[libosxunwind]** — clone of [libunwind], a library that determines the call-chain of a program. [GNU make]: http://www.gnu.org/software/make [patch]: http://www.gnu.org/software/patch [wget]: http://www.gnu.org/software/wget [m4]: http://www.gnu.org/software/m4 [awk]: http://www.gnu.org/software/gawk [gcc]: http://gcc.gnu.org [clang]: http://clang.llvm.org [python]: https://www.python.org/ [gfortran]: https://gcc.gnu.org/fortran/ [curl]: http://curl.haxx.se [fetch]: http://www.freebsd.org/cgi/man.cgi?fetch(1) [perl]: http://www.perl.org [cmake]: http://www.cmake.org [OpenLibm]: https://github.com/JuliaLang/openlibm [DSFMT]: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/#dSFMT [OpenBLAS]: https://github.com/xianyi/OpenBLAS [LAPACK]: http://www.netlib.org/lapack [MKL]: http://software.intel.com/en-us/articles/intel-mkl [SuiteSparse]: http://faculty.cse.tamu.edu/davis/suitesparse.html [ARPACK]: http://forge.scilab.org/index.php/p/arpack-ng [PCRE]: http://www.pcre.org [LLVM]: http://www.llvm.org [FemtoLisp]: https://github.com/JeffBezanson/femtolisp [GMP]: http://gmplib.org [MPFR]: http://www.mpfr.org [libuv]: https://github.com/JuliaLang/libuv [libgit2]: https://libgit2.github.com/ [utf8proc]: https://julialang.org/utf8proc/ [libosxunwind]: https://github.com/JuliaLang/libosxunwind [libunwind]: http://www.nongnu.org/libunwind [libssh2]: https://www.libssh2.org [mbedtls]: https://tls.mbed.org/ [pkg-config]: https://www.freedesktop.org/wiki/Software/pkg-config/ ### Notes for distribution package maintainers We understand that package maintainers will typically want to make use of system libraries where possible. Please refer to the above version requirements and additional notes below. It is strongly advised that package maintainers apply the patches included in the Julia repo for LLVM and other libraries, should they choose to use SYSTEM versions. A list of maintained Julia packages for various platforms is available at https://julialang.org/downloads/platform.html. ### System Provided Libraries If you already have one or more of these packages installed on your system, you can prevent Julia from compiling duplicates of these libraries by passing `USE_SYSTEM_...=1` to `make` or adding the line to `Make.user`. The complete list of possible flags can be found in `Make.inc`. Please be aware that this procedure is not officially supported, as it introduces additional variability into the installation and versioning of the dependencies, and is recommended only for system package maintainers. Unexpected compile errors may result, as the build system will do no further checking to ensure the proper packages are installed. ### LLVM The most complicated dependency is LLVM, for which we require version 3.9 with some additional patches from upstream (LLVM is not backward compatible). For packaging Julia, we recommend either: - bundling a Julia-only LLVM library inside the Julia package, or - adding the patches to the LLVM 3.9 package of the distribution. * A complete list of patches is available in `deps/llvm.mk`, and the patches themselves are in `deps/patches/`. * The only Julia-specific patch is the lib renaming (`llvm-symver-jlprefix.patch`), which should _not_ be applied to a system LLVM. * The remaining patches are all upstream bug fixes, and have been contributed into upstream LLVM. Using an unpatched or different version of LLVM will result in errors and/or poor performance. Though Julia can be built with newer LLVM versions, support for this should be regarded as experimental and not suitable for packaging. ### libuv Julia uses a custom fork of libuv. It is a small dependency, and can be safely bundled in the same package as Julia, and will not conflict with the system library. Julia builds should _not_ try to use the system libuv. ### BLAS and LAPACK As a high-performance numerical language, Julia should be linked to a multi-threaded BLAS and LAPACK, such as OpenBLAS or ATLAS, which will provide much better performance than the reference `libblas` implementations which may be default on some systems. ### Intel MKL For a 64-bit architecture, the environment should be set up as follows: # bash source /path/to/intel/bin/compilervars.sh intel64 Add the following to the `Make.user` file: USE_INTEL_MKL = 1 USE_INTEL_LIBM = 1 It is highly recommended to start with a fresh clone of the Julia repository. ## Source Code Organization The Julia source code is organized as follows: base/ source code for the Base module (part of Julia's standard library) stdlib/ source code for other standard library packages contrib/ editor support for Julia source, miscellaneous scripts deps/ external dependencies doc/src/manual source for the user manual doc/src/stdlib source for standard library function reference src/ source for Julia language core test/ test suites ui/ source for various front ends usr/ binaries and shared libraries loaded by Julia's standard libraries ## Binary Installation If you would rather not compile the latest Julia from source, platform-specific tarballs with pre-compiled binaries are also [available for download](https://julialang.org/downloads/). You can either run the `julia` executable using its full path in the directory created above, or add that directory to your executable path so that you can run the Julia program from anywhere (in the current shell session): export PATH="$(pwd)/julia:$PATH" Now you should be able to run Julia like this: julia On Windows, double-click `usr/bin/julia.exe`. If everything works correctly, you will see a Julia banner and an interactive prompt into which you can enter expressions for evaluation. You can read about [getting started](https://julialang.org/manual/getting-started) in the manual. **Note**: Although some system package managers provide Julia, such installations are neither maintained nor endorsed by the Julia project. They may be outdated and/or unmaintained. We recommend you use the official Julia binaries instead. ## Editor and Terminal Setup Currently, Julia editing mode support is available for a number of editors. While Julia modes for [Emacs](https://github.com/JuliaLang/julia-emacs), [Sublime Text](https://github.com/JuliaEditorSupport/Julia-sublime), and [Vim](https://github.com/JuliaLang/julia-vim) have their own repos, others such as Textmate, Notepad++, and Kate, are in `contrib/`. Two major IDEs are supported for Julia: [Juno](http://junolab.org/) which is based on [Atom](https://atom.io/) and [julia-vscode](https://github.com/JuliaEditorSupport/julia-vscode) based on [VS Code](https://code.visualstudio.com/). A [Jupyter](http://jupyter.org/) notebooks interface is available through [IJulia](https://github.com/JuliaLang/IJulia.jl). The [Sublime-IJulia](https://github.com/quinnj/Sublime-IJulia) plugin enables interaction between IJulia and Sublime Text. In the terminal, Julia makes great use of both control-key and meta-key bindings. To make the meta-key bindings more accessible, many terminal emulator programs (e.g., `Terminal`, `iTerm`, `xterm`, etc.) allow you to use the alt or option key as meta. See the section in the manual on [the Julia REPL](https://docs.julialang.org/en/latest/stdlib/REPL/) for more details.